Event Estimation Accuracy of Social Sensing with Facebook for Social Internet of Vehicles

© 2014 IEEE. Social Internet of Vehicles (SIoV) is a new paradigm that enables social relationships among vehicles via the Internet. People in the vehicles using online social networks (OSNs) can be an integral part of SIoV that enables the collection of data for sensing a physical phenomenon, i.e., social sensing. In this paper, we study the main social sensing mechanism in Facebook, comment thread network (CTN), which is based on the interactions of users through user walls in Facebook for SIoV. After seeing their commuters' contents about an event, users either add comments or like these posts, and Facebook CTN emerges as a social sensing medium in estimation of an event through social consensus. For the first time, this paper investigates the social sensing capability of Facebook CTN, i.e., the accuracy of collective observations for SIoV. The accuracy depends on the user characteristics and the features of the OSN, since perceptions of the users and how they use Facebook may manipulate their observation signals. We analyze the reliability of Facebook CTN for varying user behaviors, user relationships, Facebook features, and network size. The results indicate that the polarized weighting of the observations and the use of less reliable post types in CTN deteriorate the accuracy of the estimate signal, i.e., social consensus. Furthermore, the selection of users is likely to be an important factor in social sensing

Complications of limb salvage surgery in childhood tumors and recommended solutions

Bone and soft tissue malignancies are associated with serious diagnostic and therapeutic problems in every level of pubertal growth in children. Current treatment modality preferred in bone and soft tissue tumors is wide resection of tumor followed by the reconstruction of consequent defect by various methods. Chemotherapy and radiotherapy are applied for systemic effects to the patient pre- and post-operatively and for local effects that facilitate the surgical procedure. Mostly, it is very difficult to control problems following wide resection and reconstruction. In this study, our aim is to discuss the problems encountered in different resection and reconstruction approaches in childhood bone and soft tissue tumors, and the recommended solutions addressed to these problems. From 1990 to 2003, a total of 68 patients (38 female, 30 male) with a mean age of 13.1 (1.5–18) were included in the study. 85.3% of patients were diagnosed as osteosarcoma and the rest was Ewing’s sarcoma. Seventy-five percent of patients had stage IIB disease. The lesions of 34 patients were detected to be in distal femur, 26 in proximal tibia and fibula, 4 in foot and ankle joint, and the remaining 4 in pelvis. As reconstructive surgery, 40 patients had modular prosthesis, vascularized fibular graft was performed in 13 patients, and 10 patients underwent arthrodesis with vascularized fibular graft. 20.6% of patients had shortened limb, infection was detected in 4 patients, laxity in 5, and restricted motion in 4 as complication of prosthesis. With sacrificed physis, 13 patients had a mean value of 4.6 cm limb shortness. Limb salvage surgery has been considered as the gold standard treatment in orthopedic oncological surgery. More understanding of the biology of sarcoma, introduction of new effective chemotherapeutic agents, development of new techniques concerning the surgical resection, advances in diagnostic methods, and improvements in reconstructive surgery all make a major contribution to limb salvage surgery. Since some problems are still encountered, we offer a therapeutic algorithm for complications in the management of childhood tumors that we have encountered so far

Clustering in Multi-Channel Cognitive Radio Ad Hoc and Sensor Networks

© 1979-2012 IEEE. CR enables dynamic spectrum access to utilize licensed spectrum when it is idle. CR technology is applied to wireless ad hoc and sensor networks to form CRAHNs and CRSNs, respectively. Clustering is an efficient topology management technique to regulate communication and allocate spectrum resources by CR capabilities of nodes in CRAHNs and CRSNs. In this article, we thoroughly investigate the benefits and functionalities of clustering such as topology, spectrum, and energy management in these networks. We also overview motivations for and challenges of clustering in CRAHNs and CRSNs. Existing clustering schemes are reviewed and compared. We conclude by revealing key considerations and possible solutions for spectrum-aware clustering in multi-channel CRAHNs and CRSNs

Internet of Hybrid Energy Harvesting Things

© 2017 IEEE. Internet of Things (IoT) is a perfect candidate to realize efficient observation and management for Smart City concept. This requires deployment of large number of wireless devices. However, replenishing batteries of thousands, maybe millions of devices may be hard or even impossible. In order to solve this problem, Internet of Energy Harvesting Things (IoEHT) is proposed. Although the first studies on IoEHT focused on energy harvesting (EH) as an auxiliary power provisioning method, now completely battery-free and self-sufficient systems are envisioned. Taking advantage of diverse sources that the concept of Smart City offers helps us to fully appreciate the capacity of EH. In this way, we address the primary shortcomings of IoEHT; availability, unreliability, and insufficiency by the Internet of Hybrid EH Things (IoHEHT). In this paper, we survey the various EH opportunities, propose an hybrid EH system, and discuss energy and data management issues for battery-free operation. We mathematically prove advantages of hybrid EH compared to single source harvesting as well. We also point out to hardware requirements and present the open research directions for different network layers specific to IoHEHT for Smart City concept

Harvesting-throughput trade-off for wireless-powered smart grid IoT applications: An experimental study

© 2018 IEEE. Sensor nodes, one of the most crucial elements of Internet of Things (IoT), sense the environment and send their observations to a remote Access Point (AP). One drawback of sensor nodes in an IoT setting is their limited battery supply. Hereby, energy harvesting (EH) stands as a promising solution to reduce or even completely eliminate lifetime constraints of sensors with exploitation of available resources. In this paper, we propose an electric-field EH (EFEH) method to enable battery-less execution of sensor-based IoT services for Smart Grid (SG) context. For this purpose, for the first time in the literature, harvestable energy through EFEH method is investigated with a transformer room experimental set-up. Our experiments reveal that 40 mJ of energy can be harvested in a period of 900 sec with the proposed EFEH method. Building on this energy profile, we define a throughput objective function θ for a «harvest-then-transmit» type system model, to shed light on the harvesting- throughput trade-off specific to IoT-assisted SG applications. Numerical results disclose non- trivial relationships between optimal harvesting period T-H, optimal transmission period T-T and critical network parameters such as node-AP hop distance, path loss exponent and minimum reporting frequency requirement

Temporal significant wave height estimation from wind speed by perceptron Kalman filtering

The significant wave heights and periods are conventionally forecasted from the wind information on the basis of the wind-wave relationship. However, the error may become large due to many uncertainties in the wind generation prediction and wind-wave relationship. This is also confirmed by the authors, where the correlation (r) between measured wind speeds and significant wave heights is found to be 0.595 (r 2 = 0.3541). The authors have rightly mentioned the restrictive uses of regression method, especially for predicting wind generated waves. The authors have established the two layered Perceptron based on Kalman Interestingly the PKF model is a two layered network (input and output) without hidden layer. Also it is a fact that numerical or physical models have restrictions by certain assumptions and conditions, whereas artificial neural network (ANN) ha

Energy Harvesting Cognitive Radio Networking for IoT-enabled Smart Grid

© 2017 Springer Science+Business Media, LLC The Internet of Things (IoT) provides connectivity to the objects that monitor and sense the environment to integrate physical world with digital world. If IoT is enabled in the Smart Grid (SG), it can benefit from advantages of the IoT such as interoperability, connectivity, etc. By combining the IoT with energy harvesting (EH) and cognitive radio (CR) techniques, the problems of SG, such as harsh channel conditions and limited battery power, may be resolved. Hence, incorporation of EH and CR reveals a new networking paradigm for IoT-enabled SG. To this end, we first introduce CR usage in the IoT-enabled SG, and explain the advantages and challenges of CRs. Furthermore, we propose EH approaches for the resource constraint of wireless devices in the IoT-enabled SG. Operation and node architecture of energy harvesting cognitive radios (EH-CR), and network architecture of the IoT-enabled SG are described to explain details of our networking paradigm. Open issues and future research directions are discussed to enable this new paradigm

Energy Neutral Internet of Drones

Extensive use of amateur drones (ADrs) poses a threat to the public safety due to their possible misuse. Hence, surveillance drones (SDrs) are utilized to detect and eliminate potential threats. However, limited battery, and lack of efficient communication and networking solutions degrade the quality of surveillance. To this end, we conceptualize the Energy Neutral Internet of Drones (enIoD) to enable enhanced connectivity between drones by overcoming energy limitations for autonomous and continuous operation. Power provisioning with recharging stations is introduced by wireless power transfer to energize the drones. Renewable energy harvesting is utilized to realize energy neutrality, which is minimization of deficit in harvested and consumed energy in enIoD. Communication and networking architectures and protocols for realization of multi-dimensional objectives are presented. Finally, possible application areas are explained with a case study to show how enIoD operates

Selecting electrical billing attributes: big data preprocessing improvements

The attribute selection is a very relevant activity of data preprocessing when discovering knowledge on databases. Its main objective is to eliminate irrelevant and/or redundant attributes to obtain computationally treatable issues, without affecting the quality of the solution. Various techniques are proposed, mainly from two approaches: wrapper and ranking. This article evaluates a novel approach proposed by Bradley and Mangasarian (Machine learning ICML. Morgan Kaufmann, Sn Fco, CA, pp. 82–90, 1998 [1]) which uses concave programming for minimizing the classification error and the number of attributes required to perform the task. The technique is evaluated using the electric service billing database in Colombia. The results are compared against traditional techniques for evaluating: attribute reduction, processing time, discovered knowledge size, and solution quality

Prediction of electric consumption using multiple linear regression methods

In the new global and local scenario, the advent of intelligent distribution networks, or Smart Grids, allows the collection of data about the operational state of the electric network in real time. Based on this data availability, the consumption prediction becomes feasible and convenient in the short term, from a few hours to a week (temporary variables). The research proposes that the method used to present the temporary variables for a system to predict electrical consumption affects the results. To verify this hypothesis, different methods for representing these variables are considered, applied to the problem of predicting daily values of electricity consumption in the city of Bogota, Colombia